Enterprise management systems using artificial intelligence and machine learning for technical analysis

Abstract

Embodiments of the present disclosure relate to an enterprise management system that uses artificial intelligence and machine learning for technical analysis. A system may receive enterprise information associated with a client enterprise. The system may use an industry analysis model to select a query set associated with obtaining status information associated with a technical profile of the client enterprise. The system may generate client data associated with the enterprise information and the status information. The system may use matrix factorization techniques to convert the client data associated with the client enterprise into a client matrix. The system may use matrix factorization techniques to convert reference data associated with a reference enterprise into a reference matrix. The system may determine a set of scores associated with technical indicators of the technical profile based on a comparison of the client matrix and the reference matrix. The system may perform an action associated with the client enterprise based on the set of scores.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to artificial intelligence and machine learning, and more particularly to using artificial intelligence and machine learning to manage a business. Background Art

[0002] An enterprise may use various types of technology to manage the enterprise, provide services, perform operations, etc. For example, certain technologies may include various types of automation systems, software systems, computing technologies, network and communication technologies, etc. An enterprise may designate certain individuals and / or departments (e.g., information technology (IT) department, human resources (HR) department, etc.) to manage the use of technology within the enterprise and / or by certain representatives of the enterprise, depending on the individual's role or the needs of the enterprise. Summary of the Invention

[0003] In some implementations, a method includes: obtaining an industry analysis model, the industry analysis model being configured to analyze enterprises associated with a specific industry; receiving enterprise information associated with a client enterprise; using the industry analysis model, selecting a query set associated with obtaining status information, the status information being associated with a technical profile of the client enterprise; providing the query set to a client device to obtain the status information; receiving the status information from the client device; generating client data associated with the enterprise information and the status information; using matrix factorization techniques to convert the client data associated with the client enterprise into a client matrix; based on the client data, selecting reference data associated with a reference technical profile of a reference enterprise, the reference enterprise being associated with the specific industry; using matrix factorization techniques to convert the reference data into a reference matrix; determining a score set associated with technical indicators of the technical profile based on a comparison of the client matrix and the reference matrix; and performing an action associated with the client enterprise based on the score set.

[0004] In some implementations, a device includes: one or more memories; and one or more processors, communicatively coupled to the one or more memories, the one or more processors configured to: receive enterprise information associated with a client enterprise; determine enterprise characteristics associated with the client enterprise from the enterprise information; based on the enterprise characteristics, select a query set associated with obtaining status information, the status information being associated with a technical profile of the client enterprise; provide a query set to a client device to obtain status information; receive the status information from the client device; generate client data associated with the enterprise characteristics and technical indicators identified in the status information; based on the client data, select reference data associated with a reference technical profile of a reference enterprise, the reference enterprise being associated with a specific industry; generate a client matrix from the client data using a matrix factorization technique, the client matrix being based on technical indicators and enterprise characteristics; generate a reference matrix from the client data using a matrix factorization technique, the reference matrix being based on corresponding technical indicators and corresponding enterprise characteristics of the reference enterprise; determine a recommendation associated with the use of a specific technology for the technical profile based on a comparison of the client matrix and the reference matrix; and perform an action associated with the recommendation and the client enterprise.

[0005] In some implementations, a non-transitory computer-readable medium stores an instruction set, the instruction set comprising: one or more instructions that, when executed by one or more processors of a device, cause the device to: collect reference information associated with a plurality of reference enterprises, the plurality of reference enterprises being associated with a particular industry; determine technical indicators associated with the particular industry from the reference information; generate, based on the technical indicators, a query set associated with obtaining status information for the technical indicators of a client enterprise; provide the query set to a client device associated with the client enterprise to obtain status information; receive, from the client device, status information and enterprise characteristics associated with the client device; generate client data associated with the enterprise characteristics and the status information; determine, from a plurality of reference enterprises, a set of reference enterprises similar to the client enterprise based on the enterprise characteristics; obtain reference data associated with the set of reference enterprises; convert the client data into a client matrix and the reference data into a reference matrix using matrix factorization; determine, based on a comparison of the client matrix and the reference matrix, a set of scores associated with the technical indicators of the technical profile; and perform an action associated with the client enterprise based on the set of scores. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1A-Figure 1C is a diagram of an example implementation described herein.

[0007] Figure 2 is an illustration of an example environment in which the systems and / or methods described herein may be implemented.

[0008] Figure 3Is one or more Figure 2 An illustration of example components of a device.

[0009] Figure 4 is a flowchart of an example process related to techniques for enterprise analysis and integration. DETAILED DESCRIPTION

[0010] The following detailed description of example implementations refers to the accompanying drawings, in which the same reference numbers in different drawings may identify the same or similar elements.

[0011] In many cases, for various reasons, businesses are tasked with integrating one or more technologies. For example, a business may choose to go paperless to reduce waste, costs associated with paper, mailing paper, etc. As another example, a business may choose to utilize a cloud-based computing platform for day-to-day computing on behalf of a representative in order to have a centralized platform that can more easily protect, monitor, and / or share information (e.g., documents and / or files). While certain technologies continue to advance individually (e.g., becoming more efficient, more flexible, more accessible, etc.), the diversity of technologies continues to increase. More and more technology-based options are available to businesses and / or industries.

[0012] Therefore, enterprises are tasked with deciding whether certain technologies should be adopted and / or integrated with the enterprise in one form or another. Currently, many of these decisions are based on assumptions derived from an analysis of the technology (e.g., how the technology operates, what services the technology provides, etc.), a cost / benefit analysis of adopting the technology, a market analysis of the technology, and so on. However, in many cases, such analysis is performed on information that does not provide an accurate assessment of whether the technology should be adopted by the enterprise. For example, such information and / or data may be incomplete (e.g., due to the wide variety of available information), inaccurate (e.g., due to the available information being outdated), and / or irrelevant (e.g., reviews or usage information associated with users or enterprises that are not associated with or similar to the enterprise).

[0013] Some implementations described herein provide an enterprise management system that is configured to identify, determine, and / or support the integration of technologies for an enterprise based on the characteristics of the enterprise, the enterprise's technology profile, and / or technology information associated with the enterprise's industry. The enterprise management system can collect and / or maintain various technology information associated with various industries within a reference data structure to provide a centralized location for complete, accurate, and relevant information. As described herein, the enterprise management system can utilize one or more machine learning models to analyze and / or compare the above, select the most relevant information from the reference data structure, determine the best integration of a certain technology, and support the integration of the technology.

[0014] As a result, the enterprise management system can conserve computing resources (e.g., processing resources, memory resources, etc.) and / or communication resources (e.g., wireless or wired resources of a network) that might otherwise be consumed by accessing, acquiring, and / or analyzing incomplete, inaccurate, and / or irrelevant sets of information. Furthermore, the enterprise management system can allow for certain best practices (e.g., according to one or more of the models described herein) to be integrated into the enterprise, which enables the enterprise to conserve certain resources (e.g., computing resources, hardware resources, network resources, labor, etc.) that might otherwise be wasted if such best practices were not integrated.

[0015] In this way, the enterprise management system can support the recommendation and / or determination of integration of technologies. Furthermore, the enterprise management system can enable technologies to be integrated and / or utilized by the enterprise (e.g., based on information and / or resources associated with a particular technology), which prevents waste of computing resources (e.g., processing resources, memory resources, power resources, etc.) associated with computing devices that would otherwise be used by personnel to integrate the technologies.

[0016] Figure 1A-Figure 1C is a diagram of an example 100 associated with enterprise analytics and integration techniques. Figure 1A-Figure 1C As shown, example 100 includes one or more industry sources, an enterprise management system, and a client device associated with a client enterprise representative (e.g., a user of the enterprise management system). As shown in example 100, the enterprise management system includes a reference data structure, an information preprocessor, an industry analysis model, a status query data structure, a matrix generator, and an enterprise assessment model.

[0017] like Figure 1A As shown, and by reference number 105, the enterprise management system collects and tags reference information. For example, the enterprise management system can receive reference information from one or more industry sources. The industry source can include a platform (e.g., an online platform, a media platform, an application platform, an open source platform, etc.) that provides enterprise information and / or technical information to the enterprise management system (e.g., via user input, data upload, data transmission, etc.). In some implementations, the industry source can include a specific type of information source, such as a news source (e.g., a financial news source, a market news source, an industry-specific news source, etc.), a data analysis platform, a crowdsourcing platform (e.g., a survey platform, a review platform, etc.), a research platform, etc. Additionally or alternatively, the industry source can include one or more devices associated with a particular individual or organization that is communicatively coupled to the enterprise management system (e.g., via a network, such as a communication network, the Internet, etc.).

[0018] In some implementations, the enterprise management system can be configured to collect reference information from such platforms, devices, and / or other similar systems (e.g., via web crawlers, robotic process automation (RPA), Internet of Things (IoT) systems, etc.). In this case, the enterprise management system can collect reference information periodically according to a schedule and / or according to specific events (e.g., ad hoc user requests, industry-specific events, enterprise-specific events, etc.).

[0019] The enterprise management system can utilize an information preprocessor to receive reference information, process the reference information (e.g., analyze, parse, sort, etc.), and convert the reference information into a unified format for storage in a reference data structure. The information preprocessor can utilize any suitable technology to receive, process, and / or analyze the reference information. For example, the information preprocessor can utilize an application programming interface (API), optical character recognition (OCR), natural language processing (NLP), computer vision technology, etc. to process the received reference information for storage in the reference data structure.

[0020] Thus, as shown, reference information from industry sources is stored in a reference data structure. The reference information may include enterprise information identifying one or more enterprise characteristics of the reference enterprise and / or technical information identifying one or more technical profiles of the reference enterprise. More specifically, such enterprise information may include revenue information associated with the reference enterprise, growth information associated with the reference enterprise, one or more industries served by the reference enterprise, the market of the reference enterprise, the location of the reference enterprise, and the like. The technical information may include the type of technology used by the enterprise and / or the level of technology usage. The usage level may be based on a specific scale, such as a range of numbers, a maturity level (e.g., low usage, developing usage, emerging usage, strategic usage, and / or leading usage), an industry-based level (e.g., a technology-leading enterprise, a technology-intermediate enterprise, and / or a technology-lagging enterprise).

[0021] As described herein, an information preprocessor can categorize enterprise information and / or technology information for a reference enterprise into entries of a reference data structure created for, associated with, and / or specified for the reference enterprise. The information preprocessor can tag the entries with one or more identifiers and / or flags associated with example enterprise characteristics, technology profiles, etc. In this way, the reference data structure can be searchable (e.g., via an index, a chart, etc.) to permit an enterprise management system to identify entries associated with certain enterprise characteristics, technology types, technology usage levels, etc.

[0022] Thus, as an example, the information pre-processor may collect and / or receive historical surveys, historical articles, historical research documents, etc. associated with one or more businesses in one or more industries. The information pre-processor may process the historical surveys, historical articles, historical research documents to extract and / or identify business characteristics and / or technical profiles associated with the businesses, and store reference data in a reference data structure associated with the extracted and / or identified business characteristics and / or technical profiles.

[0023] In some implementations, the reference data structure may store hundreds, thousands, millions, or more pieces of reference information associated with hundreds, thousands, millions, or more reference enterprises, which may be related to different industries and / or may be associated with different types of enterprise characteristics and / or technical profiles. Additionally or alternatively, the enterprise management system may process hundreds, thousands, millions, or more sets of reference information to generate entries in the reference data structure for storage of the processed reference information.

[0024] In this manner, an enterprise management system can collect and tag reference information to permit the enterprise management system to use the reference information to determine technology-based recommendations for the enterprise and / or support integration of specific technologies for the enterprise, as described herein.

[0025] like Figure 1A As further shown, and by reference numeral 110, the enterprise management system trains the industry analysis model to identify technical indicators. The enterprise management system can periodically train the industry analysis model according to a schedule and / or based on specific events (e.g., new reference information or new entries added to the reference data structure).

[0026] The industry analysis model may include and / or be associated with one or more artificial intelligence technologies (e.g., machine learning and / or deep learning, etc.) to identify technical indicators. The technical indicators may correspond to technology-based key performance indicators (KPIs) that negatively and / or positively impact the performance of a particular enterprise. In some implementations, the technical indicators may be industry-specific. For example, the technical indicators (or KPIs) for a first industry may be different from the technical indicators for a second industry.

[0027] As described herein, an industry analytics model can be trained (e.g., according to neural network techniques, linear regression techniques, etc.) based on historical values for one or more industry parameters using historical data associated with identifying one or more technology indicators associated with the industry and / or enterprise. Such industry parameters can include KPIs for the industry, such as a revenue indicator, a growth indicator, a size indicator (e.g., representing the size of the enterprise based on the number of employees, location, value, etc.), location, market, technology profile (e.g., including usage level(s) and / or type(s) of technology being used), etc. Using historical data and values for one or more industry parameters as input to the industry analytics model, the enterprise management system can identify industry indicators for analysis related to technology integration to permit the enterprise management system to determine the optimal technology profile for the enterprise and / or the integration of one or more technologies that support the technology profile, as described herein. In some implementations, the enterprise management system (and / or another computing system associated with the enterprise management system assigned to train the industry analytics model) can retrain the industry analytics model by updating the historical data to include verified or unverified results associated with the input values for the one or more industry parameters.

[0028] In this manner, the enterprise management system can train an industry analytics model to permit the enterprise management system to analyze received enterprise information associated with a client enterprise, as described herein.

[0029] like Figure 1B As shown, and by reference numeral 115, the enterprise management system receives enterprise information from a client device. For example, a client enterprise representative (e.g., an information technology representative, a human resources representative, a management / leadership representative, etc.) can provide enterprise information via the client device in response to a message (or other communication) requesting the enterprise management system to evaluate the technical profile of the client enterprise. In some implementations, the enterprise management system can utilize one or more user interfaces and / or messaging interfaces to interact with the client device and / or the client enterprise representative, as described herein. For example, the enterprise management system can utilize a text interface, a voice interface, an instant messaging interface, a chatbot, etc.

[0030] The enterprise information may include one or more identifiers associated with the enterprise (e.g., the enterprise name, the enterprise serial number, the enterprise account number, the name or username of the client enterprise representative, etc.). Additionally or alternatively, the enterprise information may include location information associated with the client enterprise, the industry of the client enterprise, etc. The enterprise management system may be configured to provide services to the client enterprise representative, including managing the client enterprise's technology, determining the optimal technology profile for the client enterprise, and / or supporting the integration of new technology (and / or removal of old technology) for the client representative. Thus, upon receiving such a request or communication from the client enterprise, the enterprise management system may obtain the enterprise information based on characteristics of the request (e.g., the source address of the client device, the location of the client device, etc.).

[0031] In this manner, the enterprise management system can receive enterprise information associated with a client enterprise to permit the enterprise management system to determine the type of status information to be obtained from the client enterprise.

[0032] like Figure 1B As further shown in FIG, and by reference numeral 120, the enterprise management system determines technical indicators based on the enterprise information via the trained industry analysis model. For example, the enterprise management system can use the trained industry analysis model to identify certain technical indicators that may contribute (e.g., positively or negatively) to the performance of the enterprise. In some implementations, the enterprise management system can determine the technical indicators based on enterprise characteristics identified within the enterprise information and / or determined from the enterprise information (e.g., using one or more processing techniques of an information preprocessor).

[0033] In this manner, using the trained industry analysis model, the enterprise management system can determine which technical indicators of the enterprise to analyze to determine the optimal technical profile, as described herein.

[0034] like Figure 1B As further shown in FIG. 1 and referenced by reference numeral 125, the enterprise management system can retrieve industry-specific status queries associated with technical indicators via the trained industry analysis model. For example, a status query data structure can store queries that map to certain technical indicators (e.g., for certain industries). In some implementations, the queries can be retrieved and / or associated with queries used to retrieve reference data in a reference data structure (e.g., from a survey, questionnaire, poll, etc.).

[0035] The enterprise management system can select and / or generate a query set from the status query data structure that can be used to obtain status information associated with the technology indicator. For example, the query set can include specific questions about whether the enterprise uses a specific type of technology, how the specific type of technology is used, where the specific type of technology is used, when the specific type of technology is used, who uses (e.g., which departments, representatives, etc.) the specific type of technology, how long the specific type of technology has been used, etc.

[0036] In this manner, the enterprise management system can obtain industry-specific status queries associated with the most relevant status information from the enterprise relative to determining the optimal technology profile for the enterprise.

[0037] like Figure 1B As further shown in FIG, by reference numeral 130, the enterprise management system requests status information from the client device. For example, the request may include one or more messages or communications including a query set causing the client device and / or the client enterprise representative to provide status information.

[0038] In some implementations, the enterprise management system can send a response to the client device to prompt the client enterprise representative to provide status information as an answer to the query set via user input. More specifically, the query set can be provided to the client device as an electronic survey, questionnaire, etc. In some implementations, the enterprise management system can request the status information by providing a link (e.g., a uniform resource locator (URL)) to an interface (e.g., an API) that allows the client enterprise representative to provide status information.

[0039] In some implementations, the client device is configured to store and / or automatically provide status information based on receiving one or more queries from the enterprise management system. Thus, based on receipt of a selected query from the enterprise management system, the client device can respond to the request with the results of the query set. For example, for a technology indicator showing positive performance within an industry (e.g., a reference data structure includes entries showing successful reference enterprises with high technology usage), the enterprise management system can select and provide a query associated with an indication of the number of devices of a specific type associated with the technology indicator deployed within the client enterprise. In such an example, the client device can be configured to automatically perform a lookup of the number of devices and reply to the enterprise management system with the number.

[0040] In this way, the enterprise management system can request status information to permit the enterprise management system to obtain the most relevant information for determining the optimal technology profile.

[0041] like Figure 1CAs further shown in , by reference number 135, the enterprise management system generates client data based on status information received from the client device. For example, the status information may be received as a response to a request via a user interface and / or a message interface of the enterprise management system. The client data may include data and / or information extracted from the enterprise information and the status information. For example, the client data may identify enterprise characteristics (e.g., financial data (such as revenue, profit, margin, expenses, cash flow, etc.), growth data, location data, industry data, market data, size data, etc.) and technology profiles (e.g., data indicating the type of technology used, data indicating the level of technology usage, etc.) associated with the client enterprise. A technology profile may be generated or obtained from the status information based on values associated with technology indicators identified by the industry analysis model.

[0042] In this manner, the enterprise management system can generate client data from the received state information to permit the enterprise management system to evaluate the client data relative to reference data associated with a reference enterprise, as described herein.

[0043] like Figure 1C As further shown, by reference number 140, the enterprise management system selects reference data associated with the reference enterprise from the reference data structure. For example, the enterprise management system can perform a similarity analysis (e.g., using K-nearest neighbor techniques, cluster analysis techniques, etc.) to identify reference enterprises that have business characteristics similar to the business characteristics of the client enterprise (e.g., located in the same region, similar in size, similar in revenue, etc.). The reference enterprises can be identified based on a similarity score determined from a comparison of the client enterprise and a single reference enterprise associated with the same industry as the client enterprise. As described herein, a subset of the reference enterprises can receive similarity scores that meet a similarity threshold (e.g., a probability of 50% that the enterprises are similar, a probability of 75% that the enterprises are similar, a probability of 90% that the enterprises are similar, etc.). In this case, the reference data associated with the subset of reference enterprises can be selected to analyze and / or determine the optimal technical profile for the client enterprise (e.g., by determining the technical profiles of similar reference enterprises that are determined to be successful based on the reference data).

[0044] In this manner, the enterprise management system can select reference data that is most relevant to the client enterprise and that can be used to determine an optimal technology profile for the client enterprise, as described herein.

[0045] like Figure 1CAs further shown in FIG, by reference numeral 145, a matrix generator generates a matrix based on the client data and the reference data. For example, the matrix generator can use matrix factorization techniques to convert the client data and the reference data into a common format (e.g., corresponding subsets of the client data and the reference data are mapped to the same row and / or column of the matrix). As a more specific example, a technology indicator can be identified and / or indicated using an identifier (e.g., corresponding to a technology type) and a score (e.g., corresponding to a usage level) within a specific row and / or column of the matrix in another specific row and / or column of the matrix. Thus, certain rows and / or columns of the matrix can represent scores corresponding to the usage level of certain technologies by the client enterprise and / or the reference enterprise.

[0046] Therefore, the matrix generator can generate a client matrix based on technical indicators for the client enterprise and a reference matrix based on corresponding technical indicators and corresponding enterprise characteristics of the reference enterprise from the client data.

[0047] In this way, the enterprise management system can generate a client matrix and a reference matrix to permit the enterprise management system to quickly and efficiently compare client data and reference data via the enterprise assessment model.

[0048] like Figure 1C As further shown in FIG, and by reference numeral 150, the enterprise management system compares the client matrix and the reference matrix via the enterprise assessment model. For example, the enterprise management system can use one or more correlation techniques (e.g., Spearman correlation or other types of rank / order correlations) to compare the client matrix and the reference matrix, and accordingly, the client enterprises and the reference enterprises. In this case, the enterprise management system can compare the corresponding scores of the technology indicators within the matrix to identify differences between the use of various types of technology utilized within the industry.

[0049] In some implementations, based on identifying one or more reference enterprises that have achieved success within the industry (e.g., based on one or more values of a reference matrix), the enterprise assessment model can compare technology metrics for the client enterprise with the one or more reference enterprises, as shown in the client matrix and the reference matrix. Thus, if the reference matrix indicates that enterprises using a particular technology are somewhat correlated with success within the industry (e.g., particularly for enterprises of the same or similar size), the enterprise assessment model can determine that an optimal technology profile for the client enterprise should include the same or similar use of that technology.

[0050] In this manner, the enterprise management system can compare the client matrix and the reference matrix to determine an optimal technology profile for the client enterprise based on collected reference data associated with a plurality of reference enterprises.

[0051] like Figure 1CAs further shown in FIG, by reference numeral 155, the enterprise management system performs one or more actions associated with the client enterprise. For example, based on differences between the technical profile of the client enterprise and the enterprise technical profiles of successful reference enterprises, the enterprise management system may determine an optimal technical profile based on the reference technical profiles and / or enterprise characteristics of the enterprises (e.g., based on a similarity score, if one or more enterprise characteristics of the client enterprise are determined to be different from one or more reference enterprise characteristics).

[0052] Based on determining the optimal technology profile for the client enterprise, the enterprise management system can recommend (e.g., via notification to the client device or a management device of the client enterprise) that the use of a particular technology be increased. For example, the enterprise management system can generate a recommendation associated with a particular technology based on a difference between corresponding scores (or corresponding sets of scores) of the client matrix and the reference matrix (e.g., whether the use of the technology should be adjusted within the client enterprise based on a reference level of technology use by the reference enterprise). Additionally or alternatively, the enterprise management system can provide the recommendation to the client device.

[0053] In some implementations, the enterprise management system can be configured to determine and / or identify information associated with one or more technologies that integrate the optimal technology profile of the client enterprise. For example, the enterprise management system can obtain one or more offers associated with a transaction involving the use of a particular technology (e.g., an offer to sell, rent, etc.). In this case, the enterprise management system can perform a search (e.g., a database, the Internet, etc.) to find available offers and / or information about the technology that permits the client enterprise to participate in the transaction, and / or integrate the technology based on the execution of the technology. The enterprise management system can provide the offer and / or information to the client device (or management device) to support the transaction (e.g., via a link to the transaction page and / or a link to a website associated with the technology provider).

[0054] In some implementations, the enterprise management system can be configured to control the use of a particular technology. For example, with respect to cloud computing technology, the enterprise management system can be configured to adjust (e.g., increase or decrease) the use of the cloud computing technology by increasing or decreasing the cloud resources available to the client enterprise. In this manner, the enterprise management system can cause and / or execute usage transactions associated with the particular technology (e.g., transactions that activate or deactivate resources and / or pay for activation or deactivation of resources) to increase or decrease the use of the particular technology.

[0055] In some implementations, the enterprise management system can update the reference data structure with reference data associated with the determined optimal technical profile for the client enterprise. For example, the enterprise management system can store enterprise information, status information, and / or recommendations in the reference data structure. Additionally or alternatively, the enterprise management system can use the enterprise information, status information, recommendations, etc. to retrain the industry analysis model or one or more other models of the enterprise management system.

[0056] Thus, as described herein, an enterprise management system can determine an optimal technology profile for a particular enterprise and / or support the integration of technologies for the enterprise (e.g., according to an optimal technology profile) based on one or more trends or characteristics of the industry, thereby conserving resources that might otherwise be wasted by the enterprise attempting to determine an optimal technology profile and / or that might otherwise be wasted by the enterprise without integrating technologies according to the optimal technology profile, which is determined based on one or more examples described herein.

[0057] As shown above, Figure 1A-Figure 1C are provided as examples. Other examples may be related to Figure 1A-Figure 1C The number and arrangement of the devices are provided as examples, e.g. Figure 1A-Figure 1C In fact, with Figure 1A-Figure 1C There may be additional devices, fewer devices, different devices, or differently arranged devices than those shown. Figure 1A-Figure 1C Two or more devices shown in FIG may be implemented in a single device, or as Figures 1A-1C The single device shown may be implemented as multiple, distributed devices. Additionally or alternatively, as Figure 1A-Figure 1C A set of devices (eg, one or more devices) shown in FIG. 1 may perform the operations described as being performed by Figure 1A-Figure 1C Another group of devices is shown performing one or more functions.

[0058] Figure 2 2 is a diagram of an example environment 200 in which the systems and / or methods described herein may be implemented. Figure 2 As shown, environment 200 may include an enterprise management system 201, which may include one or more elements of a cloud computing system 202 and / or which may be executed within the cloud computing system 202. The cloud computing system 202 may include one or more elements 203-213, as described in more detail below. Figure 2 As further shown, environment 200 may include network 220, client device 230, and / or one or more source information devices 240. The devices and / or elements of environment 200 may be interconnected via wired and / or wireless connections.

[0059] Cloud computing system 202 includes computing hardware 203, a resource management component 204, a host operating system (OS) 205, and / or one or more virtual computing systems 206. Resource management component 204 can perform virtualization (e.g., abstraction) of computing hardware 203 to create one or more virtual computing systems 206. Using virtualization, resource management component 204 enables a single computing device (e.g., a computer, server, etc.) to operate like multiple computing devices, such as by creating multiple isolated virtual computing systems 206 from the computing hardware 203 of a single computing device. In this way, computing hardware 203 can operate more efficiently, with lower power consumption, higher reliability, higher availability, higher utilization, greater flexibility, and lower cost compared to using separate computing devices.

[0060] Computing hardware 203 includes hardware and corresponding resources from one or more computing devices. For example, computing hardware 203 can include hardware from a single computing device (e.g., a single server) or from multiple computing devices (e.g., multiple servers), such as multiple computing devices in one or more data centers. As shown, computing hardware 203 can include one or more processors 207, one or more memories 208, one or more storage components 209, and / or one or more network components 210. Examples of processors, memories, storage components, and network components (e.g., communication components) are described elsewhere herein.

[0061] The resource management component 204 includes a virtualization application (e.g., executed on hardware, such as the computing hardware 203) capable of virtualizing the computing hardware 203 to start, stop, and / or manage one or more virtual computing systems 206. For example, the resource management component 204 may include a hypervisor (e.g., a bare metal or type 1 hypervisor, a hosted or type 2 hypervisor, etc.) or a virtual machine monitor, such as when the virtual computing system 206 is a virtual machine 211. Additionally or alternatively, the resource management component 204 may include a container manager, such as when the virtual computing system 206 is a container 212. In some implementations, the resource management component 204 executes within and / or in coordination with the host operating system 205.

[0062] The virtual computing system 206 includes a virtual environment that uses computing hardware 203 to enable operations and / or processes as described herein to be performed based on the cloud. As shown, the virtual computing system 206 may include virtual machines 211, containers 212, a hybrid environment 213 including virtual machines and containers, and the like. The virtual computing system 206 may execute one or more applications using a file system that includes binary files, software libraries, and / or other resources required to execute application programs on a guest operating system (e.g., within the virtual computing system 206) or a host operating system 205.

[0063] Although enterprise management system 201 may include one or more elements 203-213 of cloud computing system 202, may be executed within cloud computing system 202, and / or may be hosted within cloud computing system 202, in some implementations, enterprise management system 201 may not be cloud-based (e.g., may be implemented outside of a cloud computing system) or may be partially cloud-based. For example, enterprise management system 201 may include one or more devices that are not part of cloud computing system 202, such as Figure 3 The device 300 may include a standalone server or other type of computing device. The enterprise management system 201 may perform one or more operations and / or processes as described in more detail elsewhere herein.

[0064] The network 220 includes one or more wired and / or wireless networks. For example, the network 220 may include a cellular network, a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a private network, the Internet, etc., and / or a combination of these or other types of networks. The network 220 enables communication between devices in the environment 200.

[0065] As described elsewhere herein, client device 230 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information associated with the enterprise's management technology. Client device 230 may include a communication device and / or a computing device. For example, client device 230 may include a wireless communication device, a user equipment (UE), a mobile phone (e.g., a smartphone or cell phone), a laptop computer, a tablet computer, a handheld computer, a desktop computer, an Internet of Things device, or a similar type of device. As described elsewhere herein, client device 230 may communicate with one or more other devices of environment 200.

[0066] Source information device 240 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information associated with technology usage within an industry, as described elsewhere herein. Source information device 240 may correspond to one or more industry sources of example 100. Source information device 240 may include a communication device and / or a computing device. For example, source information device 240 may include a database, a server, a database server, an application server, a client server, a network server, a host server, a proxy server, a virtual server (e.g., executed on computing hardware), a server in a cloud computing system, a device containing computing hardware used in a cloud computing environment, or a similar type of device. As described elsewhere herein, source information device 240 may communicate with one or more other devices of environment 200.

[0067] like Figure 2The number and arrangement of devices and networks shown are provided as examples. Figure 2 There may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or differently arranged devices and / or networks than those shown. Figure 2 Two or more of the devices shown in FIG may be implemented in a single device, or Figure 2 The single device shown in FIG200 may be implemented as multiple, distributed devices. Additionally or alternatively, one set of devices (eg, one or more devices) of environment 200 may perform one or more functions described as being performed by another set of devices of environment 200.

[0068] Figure 3 is a diagram of example components of a device 300, which may correspond to the enterprise management system 201, the client device 230, and / or the source information device 240. In some implementations, the enterprise management system 201, the client device 230, and / or the source information device 240 may include one or more devices 300 and / or one or more components of a device 300. Figure 3 As shown, device 300 may include a bus 310 , a processor 320 , a memory 330 , a storage component 340 , an input component 350 , an output component 360 , and a communication component 370 .

[0069] The bus 310 includes components that enable wired and / or wireless communication between components of the device 300. The processor 320 includes a central processing unit, a graphics processing unit, a microprocessor, a controller, a microcontroller, a digital signal processor, a field programmable gate array, an application-specific integrated circuit, and / or another type of processing component. The processor 320 is implemented in hardware, firmware, or a combination of hardware and software. In some implementations, the processor 320 includes one or more processors that can be programmed to perform functions. The memory 330 includes random access memory, read-only memory, and / or another type of memory (e.g., flash memory, magnetic memory, and / or optical memory).

[0070] The storage component 340 stores information and / or software associated with the operation of the device 300. For example, the storage component 340 may include a hard disk drive, a magnetic disk drive, an optical disk drive, a solid-state disk drive, a compact disk, a digital versatile disk, and / or another type of non-transitory computer-readable medium. The input component 350 enables the device 300 to receive input, such as user input and / or perceived input. For example, the input component 350 may include a touch screen, a keyboard, a keypad, a mouse, buttons, a microphone, a switch, a sensor, a global positioning system component, an accelerometer, a gyroscope, an actuator, and the like. The output component 360 enables the device 300 to provide output, such as via a display, a speaker, and / or one or more light-emitting diodes. The communication component 370 enables the device 300 to communicate with other devices, for example, via a wired connection and / or a wireless connection. For example, the communication component 370 may include a receiver, a transmitter, a transceiver, a modem, a network interface card, an antenna, and the like.

[0071] The device 300 can perform one or more processes described herein. For example, a non-transitory computer-readable medium (e.g., memory 330 and / or storage component 340) can store an instruction set (e.g., one or more instructions, codes, software codes, program codes, etc.) for execution by the processor 320. The processor 320 can execute the instruction set to perform one or more processes described herein. In some implementations, the instruction set executed by the one or more processors 320 enables the one or more processors 320 and / or the device 300 to perform one or more processes described herein. In some implementations, hard-wired circuits can be used in place of instructions or used in conjunction with instructions to perform one or more processes described herein. Therefore, the implementations described herein are not limited to any particular combination of hardware circuitry and software.

[0072] Figure 3 The number and arrangement of components shown in are provided as examples. Figure 3 , device 300 may include additional components, fewer components, different components, or differently arranged components than those shown in . Additionally or alternatively, one or more components of device 300 (e.g., one or more components) may perform one or more functions described as being performed by another set of components of device 300.

[0073] Figure 4 is a flow chart of an example process 400 associated with an enterprise management system for technology analysis and integration. In some implementations, Figure 4 One or more process blocks of can be executed by an enterprise management system (e.g., enterprise management system 201). In some implementations, Figure 4One or more process blocks of may be performed by another device or group of devices separate from or including the enterprise management system, such as a client device (e.g., client device 230). Additionally or alternatively, Figure 4 The one or more process blocks may be performed by one or more components of device 300 , such as processor 320 , memory 330 , storage component 340 , input component 350 , output component 360 , and / or communication component 370 .

[0074] like Figure 4 As shown, process 400 may include obtaining an industry analysis model configured to analyze enterprises associated with a specific industry (block 405). For example, as described above, the enterprise management system may obtain an industry analysis model configured to analyze enterprises associated with a specific industry.

[0075] like Figure 4 As further shown in FIG. 4 , process 400 may include receiving enterprise information associated with a client enterprise (block 410). For example, an enterprise management system may receive enterprise information associated with a client enterprise, as described above.

[0076] like Figure 4 As further shown, process 400 may include using the industry analysis model to select a set of queries associated with obtaining state information associated with the technical profile of the client enterprise (block 415). For example, the enterprise management system may use the industry analysis model to select a set of queries associated with obtaining state information associated with the technical profile of the client enterprise, as described above.

[0077] like Figure 4 As further shown, process 400 may include providing a query set to a client device to obtain state information (block 420). For example, as described above, the enterprise management system may provide a query set to a client device to obtain state information.

[0078] like Figure 4 As further shown in FIG. 4 , process 400 may include receiving status information from the client device (block 425 ). For example, the enterprise management system may receive status information from the client device, as described above.

[0079] like Figure 4 As further shown, process 400 may include generating client data associated with the enterprise information and the state information (block 430).For example, as described above, the enterprise management system may generate client data associated with the enterprise information and the state information.

[0080] like Figure 4As further shown, process 400 may include converting client data associated with the client enterprise into a client matrix using matrix factorization techniques (block 435). For example, the enterprise management system may convert client data associated with the client enterprise into a client matrix using matrix factorization techniques, as described above.

[0081] like Figure 4 As further shown, process 400 may include selecting reference data associated with a reference technical profile of a reference enterprise based on the client data, the reference enterprise being associated with a particular industry (block 440). For example, as described above, the enterprise management system may select reference data associated with a reference technical profile of a reference enterprise based on the client data, the reference enterprise being associated with a particular industry.

[0082] like Figure 4 As further shown in , process 400 may include converting the reference data into a reference matrix using a matrix factorization technique (block 445). For example, the enterprise management system may convert the reference data into a reference matrix using a matrix factorization technique, as described above.

[0083] like Figure 4 As further shown, process 400 may include determining a set of scores associated with the technical indicators of the technical profile based on the comparison of the client matrix and the reference matrix (block 450). For example, the enterprise management system may determine a set of scores associated with the technical indicators of the technical profile based on the comparison of the client matrix and the reference matrix, as described above.

[0084] like Figure 4 As further shown, process 400 can include performing an action associated with the client enterprise based on the set of scores (block 455).For example, as described above, the enterprise management system can perform an action associated with the client enterprise based on the set of scores.

[0085] Process 400 may include additional implementations, such as any single implementation or any combination of implementations described below and / or in combination with one or more other processes described elsewhere herein.

[0086] In a first implementation, the industry analytics model is a machine learning model that is trained to identify technical indicators associated with a particular industry based on historical data associated with a plurality of businesses associated with the particular industry.

[0087] In a second implementation, the machine learning model is configured to utilize natural language processing techniques to obtain historical data from at least one of the following: historical surveys of one or more of the plurality of enterprises, the historical surveys comprising one or more query sets; historical articles associated with one or more of the plurality of enterprises, the historical articles describing technology types associated with the technology profile; or historical research documents associated with one or more of the plurality of enterprises, the historical research documents describing technology types associated with the technology profile.

[0088] In a third implementation, selecting reference data includes: determining a similarity score between the enterprise information and reference enterprise information associated with the reference enterprise; determining that the similarity score satisfies a threshold indicating that the reference enterprise is similar to the client enterprise; in a reference data structure, identifying an entry in the reference data structure associated with the reference enterprise; and selecting reference data from the entry.

[0089] In a fourth implementation, the similarity scores are determined using K-nearest neighbor classification analysis.

[0090] In a fifth implementation, the technology indicator corresponds to a level of usage of a particular type of technology by a client enterprise, and wherein the set of scores is determined based on the level of usage of the particular type of technology, the level of usage of the particular type of technology being based on a corresponding reference level of usage of the particular type of technology identified in a reference technology profile.

[0091] In a sixth implementation, process 400 includes, before performing an action, identifying a score in a score set that satisfies a threshold; wherein the score in the score set is associated with a level of usage of a particular technology; and determining that the level of usage of the particular technology should be increased based on the score in the score set satisfying the threshold, wherein the action is performed to cause the client enterprise to automatically increase the level of usage of the particular technology.

[0092] In a seventh implementation, performing the action includes at least one of: generating a recommendation associated with a particular technology based on the set of scores; providing the recommendation to a management device associated with a client enterprise; obtaining an offer associated with a transaction involving use of the particular technology based on the set of scores; providing the offer to the management device to support the transaction; causing a use transaction associated with the particular technology to increase or decrease use of the particular technology; or storing the enterprise information, status information, and the recommendation in a reference data structure associated with an industry analysis model.

[0093] although Figure 4 An example block diagram of process 400 is shown, but in some implementations, Figure 4 Process 400 may include additional blocks, fewer blocks, different blocks, or blocks arranged differently than those depicted in . Additionally or alternatively, two or more blocks of process 400 may be performed in parallel.

[0094] According to some implementations, at least the following examples are provided.

[0095] Example 1. A method comprising: obtaining an industry analysis model by a device, the industry analysis model being configured to analyze enterprises associated with a specific industry; receiving enterprise information associated with a client enterprise by the device; selecting a query set associated with obtaining status information by the device using the industry analysis model, the status information being associated with a technical profile of the client enterprise; providing a query set by the device to a client device to obtain status information; receiving status information from the client device by the device; generating client data associated with the enterprise information and the status information by the device; converting the client data associated with the client enterprise into a client matrix by the device using a matrix factorization technique; selecting reference data associated with a reference technical profile of a reference enterprise based on the client data, the reference enterprise being associated with a specific industry by the device using a matrix factorization technique; determining a score set associated with technical indicators of the technical profile by the device based on a comparison of the client matrix and the reference matrix; and performing an action associated with the client enterprise based on the score set by the device.

[0096] Example 2. The method of Example 1, wherein the industry analysis model is a machine learning model trained to identify technical indicators associated with a specific industry based on historical data associated with multiple companies associated with the specific industry.

[0097] Example 3. A method according to Example 2, wherein the machine learning model is configured to utilize natural language processing technology to obtain historical data from at least one of the following: historical surveys of one or more of a plurality of enterprises, the historical surveys including one or more queries in a query set; historical articles associated with one or more of a plurality of enterprises, the historical articles describing technology types associated with a technology profile; or historical research documents associated with one or more of a plurality of enterprises, the historical research documents describing technology types associated with a technology profile.

[0098] Example 4. A method according to Example 1, wherein selecting reference data includes: determining a similarity score between enterprise information and reference enterprise information associated with a reference enterprise; determining that the similarity score satisfies a threshold, the threshold indicating that the reference enterprise is similar to the client enterprise; in a reference data structure, identifying an entry in the reference data structure associated with the reference enterprise; and selecting reference data from the entry.

[0099] Example 5. The method of Example 4, wherein the similarity score is determined using K-nearest neighbor classification analysis.

[0100] Example 6. A method according to Example 1, wherein the technology indicator corresponds to a level of usage of a particular type of technology by a client enterprise, and wherein the score set is determined based on the level of usage of the particular type of technology, the level of usage of the particular type of technology being based on a corresponding reference level of usage of the particular type of technology identified in a reference technology profile.

[0101] Example 7. The method according to Example 1 further includes: before performing the action, identifying a score in the score set that meets a threshold; wherein the score in the score set is associated with the usage level of a specific technology; and based on the score in the score set meeting the threshold, determining that the usage level of the specific technology should be increased, wherein the action is performed to enable the client enterprise to automatically increase the usage level of the specific technology.

[0102] Example 8. A method according to Example 1, wherein performing an action includes at least one of: generating a recommendation associated with a specific technology based on a set of scores; providing the recommendation to a management device associated with a client enterprise; obtaining an offer associated with a transaction involving use of the specific technology based on the set of scores; providing the offer to the management device to support the transaction; causing a use transaction associated with the specific technology to increase or decrease use of the specific technology; or storing the enterprise information, status information, and recommendations in a reference data structure associated with an industry analysis model.

[0103] Example 9. A device comprising: one or more memories; and one or more processors communicatively coupled to the one or more memories, the one or more processors configured to: receive enterprise information associated with a client enterprise; determine enterprise characteristics associated with the client enterprise from the enterprise information; based on the enterprise characteristics, select a query set associated with obtaining status information, the status information being associated with a technical profile of the client enterprise; provide a query set to a client device to obtain status information; receive the status information from the client device; generate client data associated with the enterprise characteristics and technical indicators identified in the status information; based on the client data, select reference data associated with a reference technical profile of a reference enterprise, the reference enterprise being associated with a specific industry; generate a client matrix from the client data using a matrix factorization technique, the client matrix being based on technical indicators and enterprise characteristics; generate a reference matrix from the client data using a matrix factorization technique, the reference matrix being based on corresponding technical indicators and corresponding enterprise characteristics of the reference enterprise; determine a recommendation associated with the use of a specific technology for the technical profile based on a comparison of the client matrix and the reference matrix; and perform an action associated with the recommendation and the client enterprise.

[0104] Example 10. An apparatus according to Example 9, wherein the query set is selected using a machine learning model that is trained to identify a set of technical indicators associated with one or more key performance indicators of a particular industry based on historical data associated with multiple businesses associated with the particular industry.

[0105] Example 11. A device according to Example 9, wherein when reference data is selected, one or more processors are configured to: determine a similarity score between enterprise characteristics and reference enterprise characteristics associated with a reference enterprise; determine that the similarity score satisfies a threshold, the threshold indicating that the reference enterprise is similar to the client enterprise; in a reference data structure, identify an entry in the reference data structure associated with the reference enterprise; and select reference data from the entry.

[0106] Example 12. The apparatus of example 11, wherein the enterprise characteristic and the reference enterprise characteristic are associated with at least one of: a financial indicator; a location; an industry; a market indicator; a growth indicator; or a enterprise size indicator.

[0107] Example 13. The apparatus of example 9, wherein the technology indicator corresponds to a level of usage of a particular technology associated with operating the client enterprise.

[0108] Example 14. A device according to Example 9, wherein the one or more processors are further configured to: before performing the action, identify a score in the score set that meets a threshold; wherein the score is associated with a usage level of a specific technology; and based on the score meeting the threshold, determine that the usage level of the specific technology should be increased, wherein the action is performed to cause the client enterprise to automatically increase the usage level of the specific technology.

[0109] Example 15. A non-transitory computer-readable medium storing an instruction set, the instruction set comprising: one or more instructions, which, when executed by one or more processors of a device, causes the device to: collect reference information associated with a plurality of reference enterprises, the plurality of reference enterprises being associated with a specific industry; determine technical indicators associated with the specific industry from the reference information; generate a query set associated with obtaining status information for the technical indicators for a client enterprise based on the technical indicators; provide the query set to a client device associated with the client enterprise to obtain status information; receive status information and enterprise characteristics associated with the client device from the client device; generate client data associated with the enterprise characteristics and the status information; determine a set of reference enterprises similar to the client enterprise from a plurality of reference enterprises based on the enterprise characteristics; obtain reference data associated with the set of reference enterprises; use matrix factorization to convert the client data into a client matrix and the reference data into a reference matrix; determine a score set associated with the technical indicators of the technical profile based on a comparison of the client matrix and the reference matrix; and perform an action associated with the client enterprise based on the score set.

[0110] Example 16. A non-transitory computer-readable medium according to Example 15, wherein the reference information includes at least one of the following: a historical survey of one or more of the plurality of enterprises, the historical survey including one or more queries in the query set; a historical article associated with one or more of the plurality of enterprises, the historical article describing a technology type associated with the technology profile; or a historical research document associated with one or more of the plurality of enterprises, the historical research document describing a technology type associated with the technology profile.

[0111] Example 17. The non-transitory computer-readable medium of example 15, wherein the one or more instructions that cause the device to identify a set of reference enterprises cause the device to: determine a similarity score between the enterprise characteristic and reference enterprise characteristics associated with a plurality of reference enterprises using a K-nearest neighbor technique; and

[0112] A set of reference enterprises is selected from the plurality of reference enterprises based on a set of similarity scores associated with the set of reference enterprises satisfying a similarity threshold.

[0113] Example 18. A non-transitory computer-readable medium according to Example 15, wherein the technology indicator corresponds to a level of usage of a particular type of technology by a client enterprise, and wherein the score set is determined based on the level of usage of the particular type of technology, the level of usage of the particular type of technology relative to a corresponding reference level of usage of the particular type of technology by a reference set of enterprises.

[0114] Example 19. A non-transitory computer-readable medium according to Example 15, wherein the one or more instructions further cause the device to: before performing an action, identify a score in a set of scores that satisfies a threshold; wherein the score is associated with a level of usage of a particular technology; and based on the score satisfying the threshold, determine that the level of usage of the particular technology should be adjusted, wherein the action is performed to cause the client enterprise to automatically adjust the level of usage of the particular technology.

[0115] Example 20. A non-transitory computer-readable medium according to example 15, wherein one or more instructions that cause a device to perform an action cause the device to perform at least one of the following: generating a recommendation associated with a particular technology based on a set of scores; providing the recommendation to a management device associated with a client enterprise; obtaining an offer associated with a transaction involving use of the particular technology based on the set of scores; providing the offer to the management device to support the transaction; causing a usage transaction associated with the particular technology to increase or decrease use of the particular technology; or storing enterprise characteristics, status information, and recommendations in a reference data structure associated with reference information.

[0116] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications may be made in light of the above disclosure or may be acquired from practice of implementations.

[0117] As used herein, the term "component" is intended to be broadly interpreted as hardware, firmware, or a combination of hardware and software. Obviously, the systems and / or methods described herein can be implemented in different forms of hardware, firmware, and / or a combination of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods does not limit the implementation. Therefore, the operation and behavior of the systems and / or methods are described herein without reference to specific software code - it should be understood that software and hardware can be used to be implemented based on the systems and / or methods described herein.

[0118] As used herein, satisfying a threshold may mean that the value is greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, etc., depending on the context.

[0119] Although particular combinations of features are recited in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of various implementations. In fact, many of these features can be combined in ways not specifically recited in the claims and / or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of various implementations includes the combination of each dependent claim with every other claim in the claim set.

[0120] Unless explicitly stated, any element, action or instruction used herein should not be interpreted as key or necessary. In addition, as used herein, the articles "a" and "an" are intended to include one or more items and can be used interchangeably with "one or more". In addition, as used herein, the article "the" is intended to include one or more items related to the article "the" and can be used interchangeably with "one or more". In addition, as used herein, the term "set" is intended to include one or more items (e.g., related items, unrelated items, combinations of related and unrelated items, etc.) and can be used interchangeably with "one or more". If only intended to one item, the phrase "only one item" or similar language is used. In addition, as used herein, the terms "have", "have", "having" etc. are intended to be open terms. In addition, unless explicitly stated otherwise, the phrase "based on" is intended to represent "at least partially based on". Furthermore, as used herein, the term "or" when used in serial form is intended to be inclusive and interchangeable with "and / or" unless expressly stated otherwise (e.g., if used in conjunction with "either" or "only one of").

Claims

1. A method comprising: Acquiring, by a device, an industry analysis model, wherein the industry analysis model is configured to analyze enterprises associated with a specific industry; Receiving, by the device, enterprise information associated with a client enterprise; selecting, by the device, a query set associated with obtaining state information associated with a technical profile of the client enterprise using the industry analysis model; providing, by the device, the query set to a client device to obtain the state information; receiving, by the device, the state information from the client device; generating, by the device, client data associated with the enterprise information and the status information; converting, by the device, the client data associated with the client enterprise into a client matrix using a matrix factorization technique; selecting, by the device based on the client data, reference data associated with a reference technical profile of a reference enterprise, the reference enterprise being associated with the specific industry; converting, by the device, the reference data into a reference matrix using the matrix factorization technique; determining, by the device, a set of scores associated with technical indicators of the technical profile based on a comparison of the client matrix and the reference matrix; as well as An action associated with the client enterprise is performed by the device based on the set of scores.

2. The method of claim 1, wherein the industry analysis model is a machine learning model trained to identify technical indicators associated with a specific industry based on historical data associated with multiple companies associated with the specific industry.

3. The method according to claim 2, wherein the machine learning model is configured to utilize natural language processing technology to obtain the historical data from at least one of the following: a historical survey of one or more enterprises among the plurality of enterprises, the historical survey comprising one or more queries in the query set; historical articles associated with one or more of the plurality of businesses, the historical articles describing a technology type associated with the technology profile; or A historical research document associated with one or more of the plurality of enterprises, the historical research document describing the technology type associated with the technology profile.

4. The method according to claim 1, wherein selecting the reference data comprises: determining a similarity score between the enterprise information and reference enterprise information associated with the reference enterprise; determining that the similarity score satisfies a threshold in a comparison of the characteristics of the reference enterprise and the client enterprise; identifying, in a reference data structure, an entry in the reference data structure associated with the reference enterprise; as well as The reference data is selected from the entries. The method of claim 4 , wherein the similarity score is determined using K-nearest neighbor classification analysis.

6. The method of claim 1 , wherein the technology indicator corresponds to a level of usage of a particular type of technology by the client enterprise, and Wherein the set of scores is determined based on the usage level of the particular type of technology, the usage level of the particular type of technology being based on a corresponding reference usage level of the particular type of technology identified in the reference technology profile.

7. The method according to claim 1, further comprising: Before performing the action, identifying a score in the set of scores that satisfies a threshold; wherein said scores in said set of scores are associated with a level of use of a particular technology; as well as determining that the level of usage of the particular technology should be increased based on the score in the set of scores satisfying the threshold, Wherein the actions are performed to cause the client enterprise to automatically increase the usage level of the particular technology.

8. The method of claim 1 , wherein performing the action comprises at least one of: generating a recommendation associated with a particular technology based on the set of scores; providing the recommendation to an administrative device associated with the client enterprise; obtaining, based on the set of scores, offers associated with transactions involving use of a particular technology; providing the offer to the management device in support of the transaction; Cause usage transactions associated with a particular technology to increase or decrease usage of that particular technology; or The enterprise information, the status information, and the recommendations are stored in a reference data structure associated with the industry analytics model.

9. A device comprising: one or more memories; as well as one or more processors communicatively coupled to the one or more memories, the one or more processors configured to: receiving enterprise information associated with the client enterprise; determining enterprise characteristics associated with the client enterprise from the enterprise information; selecting, based on the enterprise characteristics, a query set associated with obtaining state information associated with a technical profile of the client enterprise; providing the query set to a client device to obtain the state information; receiving the status information from the client device; generating client data associated with the enterprise characteristics and technical indicators identified in the status information; selecting, based on the client data, reference data associated with a reference technology profile of a reference enterprise, the reference enterprise being associated with a particular industry; generating a client matrix from the client data using a matrix factorization technique, the client matrix being based on the technical indicators and the enterprise characteristics; generating a reference matrix from the client data using the matrix factorization technique, the reference matrix being based on corresponding technical indicators and corresponding enterprise characteristics of the reference enterprise; determining, based on a comparison of the client matrix and the reference matrix, a recommendation associated with use of a particular technology for the technology profile; as well as An action associated with the recommendation and the client business is performed.

10. The apparatus of claim 9, wherein the query set is selected using a machine learning model trained to identify a set of technical indicators associated with one or more key performance indicators of the specific industry based on historical data associated with a plurality of businesses associated with the specific industry.

11. The apparatus of claim 9, wherein when the reference data is selected, the one or more processors are configured to: determining a similarity score between the business characteristic and a reference business characteristic associated with the reference business; determining that the similarity score satisfies a threshold in a comparison of the characteristics of the reference enterprise and the client enterprise; identifying, in a reference data structure, an entry in the reference data structure associated with the reference enterprise; as well as The reference data is selected from the entries.

12. The apparatus of claim 11, wherein the enterprise characteristic and the reference enterprise characteristic are associated with at least one of: Financial indicators; Location; industry; Market indicators; Growth indicators; or Enterprise size indicators.

13. The apparatus of claim 9, wherein the technology indicator corresponds to a level of usage of a particular technology associated with operating the client enterprise.

14. The apparatus of claim 9, wherein the one or more processors are further configured to: Before performing the action, identifying a score in the set of scores that satisfies a threshold; wherein the score is associated with a level of use of a particular technology; and determining that the usage level of the particular technology should be increased based on the score satisfying the threshold, Wherein the actions are performed to cause the client enterprise to automatically increase the usage level of the particular technology.

15. A non-transitory computer-readable medium storing an instruction set, the instruction set comprising: One or more instructions that, when executed by one or more processors of a device, cause the device to: collecting reference information associated with a plurality of reference businesses, the plurality of reference businesses being associated with a particular industry; determining technical indicators associated with the specific industry from the reference information; Based on the technical indicators, generating a query set associated with obtaining status information of the technical indicators for the client enterprise; providing the query set to a client device associated with the client enterprise to obtain the state information; receiving, from the client device, the state information and enterprise characteristics associated with the client device; generating client data associated with the enterprise characteristics and the status information; determining, from the plurality of reference enterprises, a set of reference enterprises similar to the client enterprise based on the enterprise characteristics; obtaining reference data associated with the reference enterprise set; Using matrix factorization, converting the client data into a client matrix and converting the reference data into a reference matrix; determining a set of scores associated with technical indicators of a technical profile based on a comparison of the client matrix and the reference matrix; as well as Based on the set of scores, an action associated with the client enterprise is performed.

16. The non-transitory computer-readable medium of claim 15, wherein the reference information comprises at least one of the following: a historical survey of one or more enterprises among the plurality of enterprises, the historical survey comprising one or more queries in the query set; historical articles associated with one or more of the plurality of businesses, the historical articles describing a technology type associated with the technology profile; or A historical research document associated with one or more of the plurality of enterprises, the historical research document describing the technology type associated with the technology profile.

17. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions that cause the device to identify the set of reference enterprises cause the device to: determining a set of similarity scores between the business characteristic and reference business characteristics associated with the plurality of reference businesses using a K-nearest neighbor technique; and The set of reference enterprises is selected from the plurality of reference enterprises based on a set of similarity scores associated with the set of reference enterprises satisfying a similarity threshold.

18. The non-transitory computer-readable medium of claim 15, wherein the technology indicator corresponds to a level of usage of a particular type of technology by the client enterprise, and Wherein the set of scores is determined based on the usage level of the particular type of technology relative to a corresponding reference usage level of the particular type of technology by the set of reference enterprises.

19. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions further cause the device to: Before performing the action, identifying a score in the set of scores that satisfies a threshold; wherein the score is associated with a level of use of a particular technology; and determining that the usage level of the particular technology should be adjusted based on the score meeting the threshold, Wherein the actions are performed to cause the client enterprise to automatically adjust the usage level of the particular technology.

20. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions that cause the device to perform the actions cause the device to perform at least one of: generating a recommendation associated with a particular technology based on the set of scores; providing the recommendation to an administrative device associated with the client enterprise; obtaining, based on the set of scores, offers associated with transactions involving use of a particular technology; providing the offer to the management device in support of the transaction; Cause usage transactions associated with a particular technology to increase or decrease usage of that particular technology; or The enterprise characteristics, the status information, and the recommendations are stored in a reference data structure associated with the reference information.

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